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  <div class="section" id="numpy-resize">
<h1>numpy.resize<a class="headerlink" href="#numpy-resize" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="numpy.resize">
<code class="sig-prename descclassname">numpy.</code><code class="sig-name descname">resize</code><span class="sig-paren">(</span><em class="sig-param">a</em>, <em class="sig-param">new_shape</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/numpy/numpy/blob/v1.18.1/numpy/core/fromnumeric.py#L1348-L1419"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#numpy.resize" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new array with the specified shape.</p>
<p>If the new array is larger than the original array, then the new
array is filled with repeated copies of <em class="xref py py-obj">a</em>.  Note that this behavior
is different from a.resize(new_shape) which fills with zeros instead
of repeated copies of <em class="xref py py-obj">a</em>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>a</strong><span class="classifier">array_like</span></dt><dd><p>Array to be resized.</p>
</dd>
<dt><strong>new_shape</strong><span class="classifier">int or tuple of int</span></dt><dd><p>Shape of resized array.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><strong>reshaped_array</strong><span class="classifier">ndarray</span></dt><dd><p>The new array is formed from the data in the old array, repeated
if necessary to fill out the required number of elements.  The
data are repeated in the order that they are stored in memory.</p>
</dd>
</dl>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="numpy.ndarray.resize.html#numpy.ndarray.resize" title="numpy.ndarray.resize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ndarray.resize</span></code></a></dt><dd><p>resize an array in-place.</p>
</dd>
</dl>
</div>
<p class="rubric">Notes</p>
<p>Warning: This functionality does <strong>not</strong> consider axes separately,
i.e. it does not apply interpolation/extrapolation.
It fills the return array with the required number of elements, taken
from <em class="xref py py-obj">a</em> as they are laid out in memory, disregarding strides and axes.
(This is in case the new shape is smaller. For larger, see above.)
This functionality is therefore not suitable to resize images,
or data where each axis represents a separate and distinct entity.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">],[</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">resize</span><span class="p">(</span><span class="n">a</span><span class="p">,(</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">))</span>
<span class="go">array([[0, 1, 2],</span>
<span class="go">       [3, 0, 1]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">resize</span><span class="p">(</span><span class="n">a</span><span class="p">,(</span><span class="mi">1</span><span class="p">,</span><span class="mi">4</span><span class="p">))</span>
<span class="go">array([[0, 1, 2, 3]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">resize</span><span class="p">(</span><span class="n">a</span><span class="p">,(</span><span class="mi">2</span><span class="p">,</span><span class="mi">4</span><span class="p">))</span>
<span class="go">array([[0, 1, 2, 3],</span>
<span class="go">       [0, 1, 2, 3]])</span>
</pre></div>
</div>
</dd></dl>

</div>


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